Artificial intelligence algorithms enhancing relay protection and operational efficiency in high and low voltage distribution networks

In this research project, Artificial Intelligence (AI) algorithms applied to the relay protection of high and low-voltage distribution networks are investigated. The paper attempts to solve the emerging problems caused by ever-growing complexities with dynamic characteristics of modern power systems to help solve the deficiencies of traditional protective mechanisms, which often require significant interference by personnel and consumption of resources to further increase distribution network safety, efficiency, and reliability. This research investigates using the latest worldwide algorithms to optimize circuit quality, enhance fault detection capabilities, and guarantee safety and stability in a power system operating under rigorous safety and performance standards. The study outcome showed that AI could overcome nonlinear optimization problems and multi-parameter limitations inherent in relay protection systems. The research also sheds light on the role of intelligent relay protection devices in achieving robust automation and stability of the power system, especially during various kinds of failures and variable operational cases. Experiments in research studies have shown that approaches to relay protection that AI drives ensure much higher convergence rates, operational precision, and system flexibility than traditional approaches. The investigation calls for introducing an AI-driven relay protection system as an integral part of wide-scale deployment to enhance the capabilities of smart grids so that the power distribution networks become sustainable and secure.

Authors

Institutions

Publication Details

Journal
Intelligent Decision Technologies
Published
2025-09-16
DOI
https://doi.org/10.1177/18724981251355872
Primary Topic
Power Systems Fault Detection
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial intelligence algorithms enhancing relay protection and operational efficiency in high and low voltage distribution networks

W. W. Xiao, Xinfang Ren
Intelligent Decision Technologies
Power Systems Fault Detection
article

Artificial intelligence algorithms enhancing relay protection and operational efficiency in high and low voltage distribution networks

W. W. Xiao, Xinfang Ren
article en

Abstract

In this research project, Artificial Intelligence (AI) algorithms applied to the relay protection of high and low-voltage distribution networks are investigated. The paper attempts to solve the emerging problems caused by ever-growing complexities with dynamic characteristics of modern power systems to help solve the deficiencies of traditional protective mechanisms, which often require significant interference by personnel and consumption of resources to further increase distribution network safety, efficiency, and reliability. This research investigates using the latest worldwide algorithms to optimize circuit quality, enhance fault detection capabilities, and guarantee safety and stability in a power system operating under rigorous safety and performance standards. The study outcome showed that AI could overcome nonlinear optimization problems and multi-parameter limitations inherent in relay protection systems. The research also sheds light on the role of intelligent relay protection devices in achieving robust automation and stability of the power system, especially during various kinds of failures and variable operational cases. Experiments in research studies have shown that approaches to relay protection that AI drives ensure much higher convergence rates, operational precision, and system flexibility than traditional approaches. The investigation calls for introducing an AI-driven relay protection system as an integral part of wide-scale deployment to enhance the capabilities of smart grids so that the power distribution networks become sustainable and secure.

Intelligent Decision Technologies
China Southern Power Grid (China) (CN)
Openalex Percentile: Top 69%
Power Systems Fault Detection
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.